<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Dft on Bruno Pedro</title><link>https://brunopedro.com/tags/dft/</link><description>Recent content in Dft on Bruno Pedro</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Fri, 20 Apr 2018 17:54:46 +0200</lastBuildDate><atom:link href="https://brunopedro.com/tags/dft/index.xml" rel="self" type="application/rss+xml"/><item><title>Performance oriented FFT</title><link>https://brunopedro.com/2009/07/17/performance-oriented-fft/</link><pubDate>Fri, 17 Jul 2009 11:05:55 +0000</pubDate><guid>https://brunopedro.com/2009/07/17/performance-oriented-fft/</guid><description>&lt;p>Worth checking out. Quoting the &lt;a href="http://www.fftw.org/">FFTW Home Page&lt;/a>:&lt;/p>
&lt;blockquote>
&lt;p>FFTW is a C subroutine library for computing the discrete Fourier transform (DFT) in one or more dimensions, of arbitrary input size, and of both real and complex data (as well as of even/odd data, i.e. the discrete cosine/sine transforms or DCT/DST). We believe that FFTW, which is free software, should become the FFT library of choice for most applications.&lt;/p>
&lt;/blockquote>
&lt;p>Now, can it work when you have less than 16KB available RAM?&lt;/p></description></item></channel></rss>